Thomson Reuters harnesses machine learning to screen unstructured data

Source: Thomson Reuters

Thomson Reuters has enhanced its World-Check One platform with the launch of Media Check, a unique media screening and processing feature powered by artificial intelligence (AI) that helps address the regulatory and reputational consequences of overlooking key data in the fight against financial crime.

Media Check’s machine learning capability increases efficiency by filtering unstructured content from over 11,000 global print and web sources, giving financial institutions more accurate and relevant data faster.

Thomson Reuters is committed to innovative solutions to assist its customers in the global fight against financial crime, and alleviate the considerable challenges associated with risk screening.

“Institutions need to digest an increasing amount of relevant information to help prevent financial crime. The next-generation AI technology in Media Check lets them navigate this crowded environment to help comply with regulatory and other requirements and avoid the reputational risk of missing critical information that could result in criminal activity,” said Phil Cotter, Managing Director, Risk Segment, Thomson Reuters. “Adding a machine learning dimension to our World-Check One platform gives clients an exceptional means to help pinpoint the most relevant media information, thereby maximizing the efficiency of their due-diligence processes."

World-Check One’s Media Check has many benefits that include enhanced compliance workflow, and the assurance that only relevant content is presented to compliance professionals. This is achieved through intelligent searching, a unique AML taxonomy informed by 15 years of industry leading World-Check experience, and machine learning algorithms honed by the World-Check research team. The result is a reduction in false positives and improved content navigation leading to better and more informed decision-making. Media Check also provides continuous, up-to-date media and data monitoring.

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